Web document clustering: a feasibility demonstration
Proceedings of the 21st annual international ACM SIGIR conference on Research and development in information retrieval
A Concept-Driven Algorithm for Clustering Search Results
IEEE Intelligent Systems
Clustering of search results using temporal attributes
SIGIR '06 Proceedings of the 29th annual international ACM SIGIR conference on Research and development in information retrieval
Topic Detection and Tracking for News Web Pages
WI '06 Proceedings of the 2006 IEEE/WIC/ACM International Conference on Web Intelligence
Supporting analysis of future-related information in news archives and the web
Proceedings of the 9th ACM/IEEE-CS joint conference on Digital libraries
Improving search relevance for implicitly temporal queries
Proceedings of the 32nd international ACM SIGIR conference on Research and development in information retrieval
Universal Mobile Information Retrieval
UAHCI '09 Proceedings of the 5th International on ConferenceUniversal Access in Human-Computer Interaction. Part II: Intelligent and Ubiquitous Interaction Environments
Topic segmentation algorithms for text summarization and passage retrieval: an exhaustive evaluation
AAAI'07 Proceedings of the 22nd national conference on Artificial intelligence - Volume 2
Clustering and exploring search results using timeline constructions
Proceedings of the 18th ACM conference on Information and knowledge management
Extracting collective expectations about the future from large text collections
Proceedings of the 20th ACM international conference on Information and knowledge management
ChronoSeeker: search engine for future and past events
Proceedings of the 4th International Conference on Uniquitous Information Management and Communication
Identification of top relevant temporal expressions in documents
Proceedings of the 2nd Temporal Web Analytics Workshop
Proceedings of the 21st ACM international conference on Information and knowledge management
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With the growing popularity of research in Temporal Information Retrieval (T-IR), a large amount of temporal data is ready to be exploited. The ability to exploit this information can be potentially useful for several tasks. For example, when querying "Football World Cup Germany", it would be interesting to have two separate clusters {1974,2006} corresponding to each of the two temporal instances. However, clustering of search results by time is a non-trivial task that involves determining the most relevant dates associated to a query. In this paper, we propose a first approach to flat temporal clustering of search results. We rely on a second order co-occurrence similarity measure approach which first identifies top relevant dates. Documents are grouped at the year level, forming the temporal instances of the query. Experimental tests were performed using real-world text queries. We used several measures for evaluating the performance of the system and compared our approach with Carrot Web-snippet clustering engine. Both experiments were complemented with a user survey.